“Rising acquisition costs force brands to foster long-term relationships with their customers” – a critical insight from Shopify’s 2022 Future of ecommerce report.
As the ecommerce world grows bigger and better, online merchants and their ever increasing competitors are left to face off in a fierce, untamed battle for customer loyalty.
Sadly, although the players have increased, the global audience isn’t growing at a proportional rate. Every merchant has to fight for the attention and retention of overlapping customers. Now, the lingering question is how can one win this heated battle of loyalty?
The most straightforward answer is with insight from Customer Lifetime Value (CLV).
Customer lifetime value (CLV), as a key business metric, reveals the monetary value of customer loyalty. When calculated accurately, CLV data appraises your online store’s health, and reveals the financial worth of each customer you acquire.
Without this insight, it’ll be hard to identify your most profitable customers. You’ll end up making vague business decisions based on generic sales and marketing data. This might seem okay at first, but such actions can prove to be detrimental in the long term.
That’s why determining the lifetime value of customers is crucial for every ecommerce business owner. Missing CLV data points is like walking outside at night without a flashlight: sure, you might be able to inch your way along; however, it’s just a matter of time before darkness meets gravity.
Here’s the tricky part:
There are quite a few ways to determine and analyze lifetime value of customers. Some of them are simple yet impractical; other methods are complicated and time consuming.
Beyond the mountain of CLV formulas, what decisions can you make to improve CLV for your business? Even that is shrouded in mystery and misconceptions.
So, without further ado, let’s get started.
In short, Customer Lifetime Value (CLV) is the total revenue a customer generates during their relationship with your business. In a practical sense, it reveals the worth of each customer to your business over a period of time, and not just their first purchase.
“LTV” “CLV” “CLTV” – these are some of the common abbreviations that you’ll find floating across the ecommerce cosmos. But all of these acronyms represent the same metric.
Let’s look at an example.
Lifetime Value of Customer
First Purchase
Suppose you run an online store for baby products. Sarah, a newborn mother, buys diapers from your store. After using your products for a month, Sarah falls in love with your diaper brand and decides to buy more.
At this point, many ecommerce owners will be ecstatic and end their marketing campaign as a success. But here’s the question: is Sarah truly a loyal and profitable customer?
To determine if she is one, you’ll have to wait till she completes a period of time with your business and then calculate the value she has provided. While doing so, you should consider costs of acquisition, product sold, and handling charges.
The resulting value from that calculation determines the actual worth of Sarah to your business
Now, if this value is higher than the costs spent to acquire and retain her, then you can conclude that she’s indeed a profitable customer.
We’ll look at an example of this calculation in just a little bit, but before we do that let’s understand the benefits of going through this challenge of finding customer lifetime value.
Benefits of Customer Lifetime Value (CLV)
Benefits of Customer Lifetime Value
Benefit #1 - Helps Identify Your Ideal Customer Profile
80% of Consequences come from 20% of the Causes – Pareto Principle
As an ecommerce entrepreneur, you know that only a small precious size of customers bring in the most revenue to your business. Of course it’s never going to be an exact 80/20 rule, but the Pareto Principle applies to most businesses across the world.
For example, suppose you’re running a clothing store and customers A,B, and C buy from you on month 1. They love your clothes. But for various reasons, B and C have stopped buying your products from the 5th month and possibly, moved on to your competitors.
However, customer A continues to buy with you because he finds your products trustworthy, within his budget, and resonates with his values.
Not only is he a loyal customer, but he’s probably your ideal customer profile – meaning that he’s the type of customer that will likely keep coming back to you for more.
Going back to the Pareto Principle, most ecommerce stores bank on these types of customers because they provide stability to their business and are responsible for a major chunk of their revenues.
The real challenge though, is finding these “white whale” customers, especially when you want to scale your operations and get to the next level.
It might have been difficult a few years ago, but with the best analytics solutions available today, merchants can easily find these customers by using CLV data.They can then segment their customers based on their value and use the results to make important business decisions.
Here’s the tricky part:
“Customer-centric strategies align the development and delivery of a company’s products and services with the current and future needs of its highest valued customers in order to maximize these customers’ long-term financial value to the firm.”
Peter Fader, Professor of Marketing at The Wharton School, UPenn.
Traditionally, many organizations assume they’re already customer centric, because they believe customer centricity is all about perfecting customer service or shifting corporate strategies to better align with the needs of their overall customer base.
However, Customer Centricity does not mean prioritizing all customers.
The cruel but true fact is that not all customers make an equal financial impact and therefore, do not deserve an equal share of your valuable time and resources.
While it does not mean that your worst customers should now jump ship, it clarifies that your strategies should revolve around those customers that’ll choose your brand over a competitor’s. They respond better to your products and offerings than your average customer.
Reflecting on our aforementioned example from Benefit #1, customer A is more likely to respond to your campaigns, whereas B and C will pay less attention to your efforts.
Reflecting on our aforementioned example from Benefit #1, customer A is more likely to respond to your campaigns, whereas B and C will pay less attention to your efforts.
That’s where CLV comes into picture. By using CLV, you can easily determine who these “A” customers are, and double down on targeted campaigns to retain them for a longer period and get the best ROI for your business.
You can also reduce costs of acquisition by leveraging this data and utilize the resources for experimental marketing tactics such as A/B testing
For instance, quoting our previous example, if customer A is the ideal customer, you can create a marketing campaign specifically targeting such customers for lesser cost, and use a portion of your resources to test retention strategies for customers B and C.
Typically, a good LTV (lifetime value) to CAC (customer acquisition cost) ratio is 3:1. This means for every dollar you spend on acquisition, you get $3 in return during a customer’s lifetime with your business. So if you’ve achieved this ratio with most of your customers, then take comfort knowing you’re on an upward trajectory.However, to achieve that ratio or to improve it, you will need advanced ecommerce analytics solutions such as Bloom, which will provide you with customer-specific insights and strategies for your marketing goals.
Benefit #4 - Predicts Your Future Business Based on Current CLV
The present value of future cash flows (profit) attributed to the customer relationship. – one of many definitions for CLV
Based on historical data, CLV can predict the future trends of your business
That’s why it is different from other traditional metrics such as Recency, Frequency, and Monetary Value (RFM), Past Customer Value (PCV), and Share of Wallet (SOW). To know the differences, you can check our CLV definition article where we explore deeper.
That’s why it is different from other traditional metrics such as Recency, Frequency, and Monetary Value (RFM), Past Customer Value (PCV), and Share of Wallet (SOW). To know the differences, you can check our CLV definition article where we explore deeper.
Customer Lifetime Value (CLV), as a forward-looking, predictive measurement, incorporates both the probability of a customer being active in the future and the marketing dollars to be spent to retain the customer.
To predict future CLV or expected CLV, you should consider:
- How long the customer relationship lasted (for churned customers) or is likely to last (for active and future customers);
- Number of transactions;
- Value of the transactions; and
- Other non-financial activities the customer may engage in (such as website visits, reviews, ratings, etc,.)
The CLV resulting from these calculations can then be used as a reference to make necessary decisions for profit maximization, and to minimize the chance of customers switching to competitors.
Although predicted CLV is quite necessary and useful, it’s important to recognize that it is not an ironclad way of knowing the actual time period your customer will remain active. Therefore, when predicting CLV, you must project the length of time that customers will remain active while weighing the probabilistic uncertainty around this number.
Now, let’s look at how to find CLV from your customer data.
How to Calculate Customer Lifetime Value?
As mentioned earlier, there are quite a few ways to calculate CLV, including the plethora of formulas you can find on the internet.
While every industry and business has different ways to calculate it, we will cover one of the best ways to calculate customer lifetime value in the ecommerce industry. However, for the curious hearted, here’s a list of all the formulas you can use to calculate CLV.
Now, before we start, you should know that CLV can be calculated for both non-subscription and subscription based ecommerce businesses. Here’s what we mean by that:
Here’s what we mean by that:
- Non-Subscription based E-commerce
Most e-commerce business models are non-subscription based models. Means the customers get on to a merchant site, make a purchase, and leave. They’re not subscribing to a recurring product delivery.
For example, if your store sells denims and t-shirts then your customers are going to buy a few clothes and then return when they need more. You may not get repeat purchases very often from a single customer.
Hence it’s considered as a non-subscription ecommerce business.
Here’s an extensive article we’ve written on how to calculate CLV for non-subscription based ecommerce businesses.
- Subscription based E-commerce
On the contrary, any ecommerce business that offers products for a weekly or monthly recurring fee are considered as subscription models.
The best example for this is Dollar Shave Club, who offer a different range of razors to their customers on a monthly subscription basis.
If you have created a business model where customers can pay a fee for timely (daily, weekly, or monthly) delivery of your products, then it’s considered as a subscription business.
Generally, it’s a bit convenient to gauge CLV for subscription and contractual based businesses as finding when a customer stops buying your products is easier. Here’s an article discussing CLV calculation for subscription e-commerce.
Now let’s look at how to calculate customer lifetime value and the various formulas & steps used during this process.
Customer Lifetime Value Formula
To accurately calculate Customer lifetime value, you need to factor in multiple metrics. Unfortunately it is not as easy as Average Order Value X Number of Purchases per Year X Number of Years as Customer.
Even though it’s the formula you’ll find in almost every place on the internet, such calculations are too simplistic and you can never take critical decisions based on it.
So, with that said, here are all the formulas that we will be using to calculate CLV, for both subscription and non-subscription types.
Rate of Retention
Rate of retention gives the percentage of customers that you’ve retained after their first purchase.
Rate of Retention = No of Customers Retained / Number of Customers
Churn Rate
Customer churn rate shows the percentage of customers that we’ve lost since the first purchase.
Churn Rate = 1 – (Rate of Retention)
Average Order Value (AOV)
Average order value, as the name suggests, is the average value of orders from the revenue generated during the period.
Average Order Value (AOV) = Revenue / Number of Orders
Cost of Goods Sold (COGS)
There are two ways to calculate COGS.
COGS = Product Cost + Shipping Cost + Maintenance – This formula is best for resellers.
COGS = Beginning Inventory + Purchases in Current Period – Ending Inventory – This formula is best for manufacturers.
Customer Acquisition Cost (CAC) Per Customer
CAC is the most important metric required to calculate CLV. It reveals the cost to acquire each customer or a group of customers within a cohort.
CAC = Total Cost / Total Customers Attained
Revenue
Revenue made before costs, within the time period of the cohort, is required for further calculations.
Revenue = Number of Orders * Average Order Value
Gross Profit
Determines the profit after the costs.
Gross Profit = Revenue – COGS (product cost)
Customer Lifetime Revenue
Finding the lifetime revenue of a customer is necessary before finding the lifetime value of each customer.
Lifetime Revenue = Revenue – Product Costs – CAC – Handling Costs
Cumulative CLV
Cumulative CLV is an addition of each month-on-month lifetime revenue.
Cumulative CLV = Month + Month
Per Customer Lifetime Value
This is the final step in the calculation that reveals the gold number, which is the CLV.
Per Customer LTV = Cumulative CLV / Number of Customers Originally Acquired.
Now that we have all the formulas that will help us determine the CLV correctly, let’s look at the calculation of CLV with an example.
Customer Lifetime Value Calculation (With Example)
Let’s imagine you ran a marketing campaign and acquired 100 customers in the month of February and earned a revenue of $500 from first-time purchases.
Now we need to know how many of these 100 customers have been retained and their per customer LTV over a period of 5 months. Here are the 10 steps on how to achieve it.
Step 1: Find out Customer Acquisition Cost
We need to first start by finding out Customer Acquisition Cost (CAC). For this example, we have total ad spend (CAC) at $200.
And the CAC per customer (Total Cost / Total Customers Attained) is $2
Step 2: Calculate Average Order Value
The Average order value (Revenue / Number of Orders) for a revenue of $500 and 100 orders is $5.
Step 3: Determine the Cost of Goods Sold (COGS)
To keep this example simple and to avoid complexities, we’ve set the COGS to be a constant 40% of the revenue.
Step 4: Calculate the Rate of Retention
Now, let’s determine the rate of retention of the customers acquired in Feb 2021 over a period of 5 months. The formula will be Rate of Retention = No of Customers Retained / Number of Customers.
Step 5: Calculate the Churn Rate
Next, we need to calculate the churn rate of each customer: 1 – (Rate of Retention).
Step 6: Calculate the Revenue Over 5 Months
We then calculate the gross revenue of the retained customers by using the formula Revenue = Number of Customers * Average Order Value.
Step 7: Determine Cost of Goods Sold (COGS)
As mentioned earlier, for this example, COGS is set to a constant 40%. However, to calculate COGS, you can use COGS = Beginning Inventory + Purchases in Current Period – Ending Inventory.
Considering that COGS remains the same, the formula will be Revenue * COGS%.
Step 8: Find the Gross Profit and Gross Margin
We then calculate the gross profit and gross margin.
The formula for Gross Profit is Revenue – COGS (product cost) and the formula for Gross Margin is (Gross Profit / Revenue) X 100.
Step 9: Find the Lifetime Revenue
Generally, there is an additional step here where you figure out the CAC. However, in this example, as we’re not spending any additional costs to retain the customers acquired, the CAC from month 1 through 5 will be 0.
Once CAC is figured out, it’s time to calculate Lifetime Revenue. The formula for that is Lifetime Revenue = Revenue – COGS (Product Costs) – CAC – Handling Costs. You can ignore handling costs as we don’t have it as part of this calculation.
Step 10: Calculate Cumulative CLV and Per Customer LTV
It is finally time to calculate CLV. To determine Cumulative CLV, use Month + Month. That is Month 0 + Month 1, Month 1 + Month 2, and so on. To determine Per Customer Lifetime Value, use Cumulative CLV / Number of Customers Originally Acquired.
Finally, with the aid of all the above numbers, we’ve found the per customer lifetime value of this set of customers as $9.10.
The LTV/CAC is at 4.6, which is a pretty good ratio.
And that’s how you can calculate the customer lifetime value for e-commerce businesses which work on a subscription basis.
Download the Spreadsheet for CLV Calculation in Ecommerce Stores.
So we’ve learned how to find lifetime value of each customer from a group of customers. However, in real time, you’d want to analyse CLV of customers based on sales, sales margins, transactions, and orders.
You’d also analyze these metrics by time periods (such as 6 months to 2 years) and by timeframes (such as weeks, months, quarters, and years).
To do that, you’d need a much more complex and efficient method that can provide accurate information. And among the various methods available, the most popular and effective one is Cohort Analysis.
Cohort analysis is a time-tested method to analyze customers and the value they provide to your business. It separates customers into groups (cohorts) and helps you track each cohort from their first order through their lifetime.
Advanced applications such as bloom analytics enable you to get the best insights from this analysis with the help of AI and machine learning.
Not only does cohort analysis estimate the past and present CLV of your customers but it can also help you predict the future CLV.
In our definitive guide on cohort analysis, we’ve covered every aspect of Cohort analysis and how one can use it to determine lifetime value.
Now, let’s look at a simple example of how to analyze lifetime using cohort analysis.
In the above sample, we have 6 cohorts which show live data from a Shopify store. These cohorts are from Jan 2021 to Jun 2021.
Each row represents a cohort of customers. For example, Mar 2021’s row shows all the new customers acquired in that month and their lifetime value for the next two months.
Each column (except for new customers and first order columns) displays CLV from month 0 to the latest month of that particular cohort.
When you look at a cohort from left to right, it shows if the lifetime value is growing or declining. When you look from top to bottom, you can analyze how each cohort is performing month-on-month.
Now when you look at this data diagonally, it shows the data of all the customers for a specific month.
For example, if you start at June 2021 cohort’s month 0 and look at it diagonally till Jan 2021 cohort’s Month 5, it shows the CLV of all the customers from Jan to June 2021.
Essentially, you’re able to look at CLV in three different angles, and these trends and behaviors can provide a lot of insight into retention, repeat purchase rate, and various other metrics.
In a nutshell, cohort analysis makes it easier to:
- Break vast amounts of data into well defined groups
- Spot trends between different groups
- Determine customer retention rate
- Track customer behaviour that’s affecting lifetime value
And that’s why Cohort analysis is the answer to accurate CLV.
The process of increasing your CLV could be as easy as making minor changes to your product markups or as difficult as changing your entire customer support process.
But here are 5-proven ways that can help you increase your customer lifetime value.
Offer Exceptional Customer Support
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Provide Omni-Channel Assistance
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Stay dedicated and provide support around the clock to s
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Use chat-boats for repeat questions
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